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THE RELATIONSHIP OF SOIL PROPERTIES 
AND THE GROWTH OF RED CEDAR 
IN PLANTATIONS 

BY 


ROY H. LEDFORD 



DUKE 

UNIVERSITY 



LIBRARY 













V 



Duke University Library 


The use of this thesis is subject to the usual restrictions that 
govern the use of manuscript material. Reproduction or quotation 
of the text is permitted only upon written authorization from the 
author of the thesis and from the academic department by which it 
was accepted. Proper acknowledgment must be given in all printed 
references or quotations. 

FORM 412 1 M 11-43 


THE RELATIONSHIP OF SOIL PROPERTIES AND THE 
GROWTH OF RED CEDAR IN PLANTATIONS 


by 

Roy H. Ledford 


Date: 

Approved: 



/f-TZ- 



A thesis 

submitted in partial fulfillment of 
the requirements for the degree 
of Master of Forestry in 
the School of Forestry 
of 

Duke University 


1951 



Digitized by the Internet Archive 

in 2019 


https://archive.org/details/relationshipofsoOOOOIedf 


Ta rw. 

#0. F. 


ACKNOWLEDGEMENTS 


The author wishes to express his 
appreciation of the contributions of Dr. 

T. S. Coile in suggesting the problem to 
be studied and in reviewing this manuscript. 
The author is also indebted to Professor 
F. X. Schumacher for advice on statistical 
analysis of data. 


R. H. L. 


O r* 

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TABLE OF CONTENTS 


Introduction. ............. 2 

Previous Work ............ . 3 

Field Procedure . ...... 6 

Laboratory Procedure. ......... 9 

Statistical Analysis. ........ .11 

Observations and Conclusions. .... .18 

Summary ........ . . . .20 

Appendix. ............... 21 

Literature Cited. .......... .28 


0 .1 0 u <J u 










































THE RELATIONSHIP OF SOIL PROPERTIES AND THE 


GROWTH OF RED CEDAR IN PLANTATIONS 










INTRODUCTION 


Marked variations have been noted in the growth of young 
plantations of eastern red cedar ( Junlperus virglnlana L.). 
Although forest sites have been evaluated from the standpoint 
of older trees, little Is known about site conditions which 
make differences In growth of young trees. This is true because 
height growth of trees in young stands or plantations is fre- 
quently similar despite differences in site conditions. 

This study was made for the purpose of determining what 
soil factors are significant in the growth of young red cedar 
in plantations. Observed soil features and height growth are 
shown on maps of both plantations studied. Other data such as 
diameter of the trees at breast height, percent rock of the 
subsoil, and "imbibitional water value" of the B horizon are 
shown in tabular form. It is believed that features incorporated 
in the final regression equation can be easily recognized and 
measured In the field. 


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PREVIOUS WORK 


Site quality has received considerable attention in recent 
years as a criterion for classification of forest land according 
to its productivity. The necessity of some estimate of site 
quality of bare land or areas containing young stands of timber 
has been recognized. 

Research along these lines has met with varying degrees of 
success. The quality of a given site may be influenced by any 
of the following factors: climate, topography, range of species, 
and characteristics within the soil profile. Climate influences 
amount and distribution of precipitation. Topography influences 
slope, and direction of slope or exposure. Characteristics 
within the soil profile determine amount and quality of growing 
space for plant roots with respect to: 

a. water 

b. nutrients 

c. aeration.^ 


1. From a lecture by T. S. Coile, Duke University, 19^8. 


C3] 



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4 

Soil profiles have become recognized as a most reliable 
means for determining site quality within a given locality. 
Climate variations and range of species generally take place 
over larger areas than do local variations in soil profile con¬ 
ditions. 

Studies made by Celle (1948) indicated that the soil 
variables most significant in the estimation of site index were 
depth of the A horizon and the imbibltional water value of the 
B horizon. As a result, he formulated regression equations 
which gave very satisfactory estimates of site index. He 
developed formulas for determining site index of loblolly and 
shortleaf pine as follows: 

75 

S.I. Loblolly = 100.04 - ^ - 1.39(x 9 ) 

S.I. Shortleaf = 77-32 - - 1.00(x 9 ) 

where: x^ = depth of A horizon 

x^ sb imbibltional water value of B horizon 

Later, new equations were formulated which took into 
account corrections for differences in “Northern Piedmont” and 
"Southern Piedmont." 

New soil-site regression equations are: 

A. Loblolly Pine 

Log (Y l ) = 2.0188 - %|22 - 0.00843 (xg) - °-^ 8 




, • 




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. 

, . 




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: 






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5 


B. Shortleaf Pine 

Log (Y s ) = 1.8782 + 0.0339 (N) - M ] _ 

0.007059 (xj) - — 

where: Y = estimate of site index in feet on its log 

= depth of A horizon in inches 
x^ = imbibitional water value of the B horizon 
and N is +1 for the “Northern Piedmont” 

“1 for the “Southern Piedmont.” 

Arend and Oollins (1948) found depth of the soil to be the 
principal site factor measured that affects the growth and 
character of natural stands of eastern red cedar on upland 
soils in the Ozarks. Soil depth was defined as either the depth 
of the soil solum to unconsolidated parent rock material or 
layers that are easily penetrated by plant roots. Exposure and 
topographic position were found to affect the character of red 
cedar stands but not total growth and yield. The difference in 
soil type was considered relatively unimportant except where 
influenced by soil depth. 

Roberts (1939) found that Increase in depth of surface soil 
favored height growth of black locust plantations in Mississippi. 
By surface soil, he meant the A horizon down to clay material. 






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FIELD PROCEDURE 

Two red cedar plantations were examined in this study. A 
map was made of each plantation showing soil features and growth 
attained up to time of mapping. 

Plantation 1 

This plantation is located in the New Hope Creek Division 
of Duke Forest, Compartment 14, Stand 5* The area is 9.6? acres. 
The following information is shown on the map on page 22 of the 
Appendix: 

1. Soil series 

2. Depth of A horizon 

3» Degree of stoniness 

4. Average height range of trees 

The sampling procedure was on a four tree composite sample 
basis. In the center of each of the 57 delineations, a sample 
plot of four trees was taken and subsoil samples collected on 
the north side of each tree at one-half the crown radius. These 


[ 6 ] 





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7 

samples were mixed and taken to the laboratory for moisture- 
and xylene equivalent determinations. At the time the B horizon 
samples were taken the depth of the A horizon was measured to 
the nearest tenth of an inch. Also each tree was measured for 
total height and d.b.h. These data are shown in average form 
in Table 1 of the Appendix. Age was determined by borings and 
office records. 

Plantation 2 

This area is located in the Durham Division of Duke Forest, 
Compartment 21, Stand 28. The total acreage is The 

map of this plantation contains the following informations 

1. Soil series 

2. Texture of A horizon 

3. Depth of A horizon 

4. Average range of tree heights 
This map is shown on page 2 6 of the Appendix. 

Sampling Methods 

A plot containing nine trees was selected in the center of 
each of the 16 delineations. This was generally within a 
12 x 12 foot square. Each tree was measured for total height 
to the nearest tenth of a foot, and for diameter at breast 
height to the nearest tenth of an inch. While recording these 
data, depth of the surface soil was measured at each tree, and 



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8 


is shown in average form in Table 2 of the Appendix, A sample 
of the B horizon was taken for laboratory determinations of 
moisture- and xylene equivalents. 

In taking subsoil samples, care was taken to get the soil 
from well within the B horizon but not too deep. 








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LABORATORY PROCEDURE 


Laboratory determinations were made on all soil samples from 
each plantation for the purpose of establishing the Imbibitional 
water values. The imbibitional water value is the difference 
between moisture equivalent and xylene equivalent. These tests 
were run on air“dry soil that passed through a two millimeter 
sieve. Duplicate observations were made on each sample. 

The moisture equivalent is the amount of water retained by 
a sample of soil which has been saturated with water, after It 
has been subjected to a force 1,000 times gravity for 40 minutes. 
After centrifugation the samples were weighed and dried at a 
temperature of 105° C. The moisture equivalent was computed on 
a percentage basis as follows? 

M.E. = loss In weight of water x 100 
weight of oven-dry soil 

Xylene equivalents were determined in much the same manner, 
except that xylene was used instead of water. Since xylene is 
a non-polar liquid, it is not imbibed by colloidal particles 
nor is it adsorbed upon the surfaces of negatively charged soil 






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10 


colloids. Xylene that remains In the soil after centrifugation 
is in the smaller capillary pores. Water, being a polar liquid, 
Is attracted to these surfaces and may enter the interstitial 
spaces of some soil colloids. A correction was made for the 
specific gravity (0.86) of xylene in order to place It on a 
water basis. Xylene equivalents were determined in the following 
manner: 

X f - loss in weight of xylene/0.86 
* ' * ~ weight of oven-dry soil 

All imbibitional water values (x^) are shorn in the Appendix, 
Tables 1 and 2. 








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STATISTICAL ANALYSIS 


Subsequent regression analysis was made of data shown in 
the Appendix, Tables 1 and 2. The meanings of symbols used 
throughout are as follows? 

w = weight of plot sampled 

X X =s (up to final regression equation) 

x - — —- (in final regression equation) 
l age +1 

X 2 ” depth of A horizon 

imbib ltlonal water value 
X 3 “ 100 

y = log of observed height 
ck = w 4- xi + x 2 + + y 


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12 


Plantation 1 
First Normal Equation 


Plot 

No. 

w 

X 1 

x 2 

x 3 

y 

ck 

1 

1 

.07 

.06 

.29 

1.21 

2.63 

2 

1 

.07 

.17 

.26 

.86 

2.36 

3 

1 

.07 

.26 

.26 

.73 

2.32 

4 

1 

.07 

.2? 

.23 

.74 

2.31 

5 

1 

.07 

.10 

.24 

1.17 

2.58 

6 

1 

.07 

.18 

.25 

.87 

2.37 

7 

1 

.07 

.26 

.25 

.72 

2.30 

8 

1 

.07 

• 33 

.25 

-75 

2.40 

9 

1 

.07 

.17 

.21 

.86 

2.31 

10 

1 

.07 

.30 

.23 

.51 

2.11 

11 

1 

.08 

.18 

.25 

.88 

2.39 

12 

1 

.08 

.27 

.22 

.74 

2.31 

13 

1 

.08 

.18 

.26 

.89 

2.41 

14 

1 

.08 

.09 

.21 

1.06 

2.44 

15 

1 

.08 

.18 

.21 

.75 

2.22 

16 

1 

.08 

.16 

.22 

1.02 

2.48 

17 

1 

.08 

.14 

.16 

• 96 

2.34 

18 

1 

.08 

.18 

.17 

.96 

2.39 

19 

1 

.08 

.11 

.18 

.84 

2.21 

20 

1 

.08 

.18 

.22 

.88 

2.36 

21 

1 

.08 

• 13 

.23 

.88 

2.32 

22 

1 

.08 

.29 

. 16 

.4? 

1.95 

23 

1 

.08 

.18 

.20 

.84 

2.30 

24 

1 

.08 

.15 

.17 

.96 

2.36 

25 

1 

.08 

.20 

.18 

.95 

2.41 

26 

1 

.08 

.13 

.08 

1.07 

2.36 

27 

1 

.08 

.10 

.12 

1.12 

2.42 

28 

1 

.08 

.31 

.19 

.50 

2.08 

29 

1 

.08 

.30 

.09 

.48 

1.95 

30 

1 

.08 

.18 

.12 

. .82 

2.20 

31 

1 

.08 

.18 

.11 

1.06 

2.43 

32 

1 

.08 

.17 

.0? 

.97 

2.29 

33 

1 

.08 

.20 

.0? 

.71 

2.06 

34 

1 

.08 

.18 

.13 

.87 

2.26 

35 

1 

.08 

.10 

.12 

1.05 

2.35 

36 

1 

.08 

.19 

.08 

.86 

2.21 

37 

1 

.08 

.14 

.07 

1.05 

2.34 

38 

1 

.08 

.09 

.12 

.98 

2.27 

39 

1 

.08 

.08 

.06 

1.14 

2.36 

40 

1 

.08 

.13 

.07 

1.04 

2.32 

41 

1 

.08 

.20 

.07 

.82 

2.17 

42 

1 

.08 

.20 

.08 

.80 

2.16 

43 

1 

.09 

.41 

.09 

.55 

2.14 

44 

1 

.08 

.15 

.08 

1.05 

2.36 

45 

1 

.08 

.17 

.09 

.84 

2.18 
















































13 


Plantation 1 

First Normal Equation (Continued) 


Plot 

No. 

w 

x i 

x 2 

x 3 

y 

ck 

46 

1 

.09 

.15 

.10 

.86 

2.20 

47 

1 

.09 

.23 

.05 

.7 6 

2.13 

48 

1 

.08 

.13 

.08 

1.04 

2.33 

49 

1 

.09 

.17 

.07 

.87 

2.20 

50 

1 

.09 

.14 

.08 

.98 

2.29 

51 

1 

.09 

.17 

.09 

.98 

2.33 

52 

1 

.09 

.25 

.09 

.85 

2.28 

53 

1 

.09 

.14 

.09 

1.06 

2.38 

54 

1 

.09 

.11 

.29 

.96 

2.40 

55 

1 

.09 

.13 

.24 

.87 

2.33 

56 

1 

.10 

.21 

.18 

.73 

2.22 

57 

1 

.10 

.29. 

. 23 

.40 

2.02 


57 

4.60 

io.4o 

8.96 

49.64 

130.60 


S 

S 

s 

S 

S 

ck S 

Second normal equation: 

S(x x 2 ), 

S(x x x 2 ), 

S(x 1 X 3 ) , S(x]_y), S(x^ck) 

Third 

normal equation: 

S(x 2 2 ), 

S(x 2 x^), 

S(x 2 y), S(x 

2 ck) 

Fourth normal equation: 

SU 3 2 ), 

Sfx^y), SCx^ck) 



w wx^ 

wx 2 

WX 3 

wy 

wck 

1 

57 4 .60 10.40 

8.96 

49.64 

130.60 

X x 

0.3740 

0.8400 

0.7H7 

3.9970 

10.5227 

X 2 



2.1652 

1.6612 

8.4697 

23.5361 

X 3 




1.7002 

7.6890 

20.7221 

y 





45.0602 

114.8559 




















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14 


Plantation 2 
First Normal Equation 


Plot 

No. 

w 

X 1 

x 2 

x 3 

y 

ck 

1 

1 

.10 

.04 

.07 

1.05 

2.26 

2 

1 

.10 

.06 

.08 

1.07 

2.31 

3 

1 

.10 

.08 

.09 

• 98 

2.25 

4 

1 

.10 

.05 

.08 

1.12 

2.35 

5 

1 

.10 

.06 

.0? 

1.06 

2.29 

6 

1 

.10 

.04 

.08 

1.11 

2.33 

7 

1 

.10 

.11 

.09 

.89 

2.19 

8 

1 

.10 

.06 

. 06 

• 95 

2.17 

9 

1 

.10 

.09 

.07 

• 93 

2.19 

10 

1 

.10 

.18 

.11 

• 75 

2.14 

11 

1 

.10 

.04 

.05 

• 75 

1.94 

12 

1 

.10 

• 03 

.05 

• 59 

1.72 

13 

1 

.10 

• 09 

.06 

• 99 

2.24 

14 

1 

.10 

.08 

.08 

.96 

2.22 

15 

1 

.10 

• 07 

.06 

1.04 

2.27 

16 

1 

.10 

.05 

. 06 

1.12 

2.33 


16 

1.60 

1.13 

1.16 

15.31 

35.20 

Second 

normal 

equation: 

S(x 1 2 )» 

S(x 1 x 2 ), 

S(x x x^), Sfx-jy) 

, S(x x 

Third ] 

normal 

equation: 

S(x 2 2 ), 

S(x 2 x 3 ), 

S(x 2 y), S(x 2 ck) 


Fourth 

normal 

equation: 

S(x 3 2 ), 

S(x^y), S(x^ck) 




w 

WXi 

wx 2 

wx 3 

wy 

wck 

1 

16 

1.60 

1.13 

1.16 

15.31 

35.20 

X 1 


0.1600 

0.1130 

0.1160 

1.5310 

3.5200 

X 2 



0.0999 

0.0883 

1.0631 

2.4943 

x 3 




0.0880 

1.1149 

2.5672 

y 





15-0317 

34.0507 







































































15 


All data was combined and computed as follows: 


DF 


w wxx 

wx 2 

WX3 

wy 

wck 


1 

73 6,2000 

n.5300 

10.1200 

64.9500 

165.8000 


X 1 

0.5340 

0.9530 

0.8277 

5.5280 

14.0427 

73 

x 2 


2.2651 

1.7495 

9.5328 

26.0304 


x 3 



1.7882 

8.8039 

23.2893 


y 




60.0919 

148.9066 


x i 

0.0074 

=0.0263 

=0.0318 

0.0117 

=0.0390 

72 

*2 

x 3 


0.4440 

0.1511 

0.3853 

-0.7257 

-0.2001 

=0.1569 

0.3045 


y 




2.3042 

1.3901 


x 2 


0.3505 

0.0381 

=0.6841 

-0.2955 

71 

x 3 



0.2486 

=0.14-98 

0.1369 


y 




2.2857 

1.4518 

70 

x 3 

y 



0.2445 

-0.0754 

0.9505 

O.I69I 

0.8751 

69 

y 




0.9272 

0.9272 

































16 


Analysis of Variance 


Source 

Degrees of 
Freedom 

Sums of 
Squares 

Mean 

Square 

Residual on x^ 

1 

0.0185 

0.0185 

Added effect of x 2 

1 

1.3352 

1.3352 

Added effect of xj 

1 

0.0233 

0.0233 

Residuals 

69 

0.9272 

0.0134 

Total 

72 

2.3042 



x 2 is highly significant 
x^ is not significant 


After eliminating x 2 , additional mean squares due to 

x^ = 0.1689 


0.1689 
“ 0.0134 


This is highly significant, 
but after eliminating x 2 . 


Unknowns: 


Constant: 1.652500 
Coefficient of x^: =5.351351 
Coefficient of x 2 : -!•951783 


ck 


The final form of the regression equation used is as 
follows: 


y = b 0 + bjxx + b 2 x 2 

where: Y = calculated log of height 

b 0 = constant 
bi = coefficient of x^ 
b 2 = coefficient of x 2 















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17 


Y = 1.6525 - 5.3514 x x ~ 1.9518 x 2 

Since the current growing season was not included in age 

data, xt must now be considered as — ~ * . 
x age + 1 









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OBSERVATIONS AND CONCLUSIONS 


The most significant soil variable measured was depth of the 
A horizon (x£). The imbibitional water value of the B horizon 
(x^) was non-signifleant when tested with the depth of the A 
horizon. Since proof has been established of the relation of 
the imbibitional water value of the B horizon to site Index, 
it is only logical to conclude that the trees in this study were 
not of sufficient age to make this variable significant. On 
the other hand, it is reasonable to believe that depth of 
surface soil is pertinent because the feeder roots of plants 
have more room to develop in a deeper surface soil. 

Some influence of degree of stoniness on growth might be 
suspected by a study of Table 1 in the Appendix. For example, 
in comparing plots number 27 and 35; it is found that although 
the A horizon of plot 35 is deeper and the x^ value is lower, 
plot 27 has a higher average growth of 2.10 feet. The d.b.h. 
of plot 27 is higher by 0.88 inch. This seems reason enough to 
believe that degree of stoniness had some effect in this 
particular example. This factor was recorded, but not introduced 


[18] 


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19 


into the regression as a variable because of the infrequent 
occurrence of this condition. This also may have been a factor 
in the growth attained on plot number one. 

Slope is another factor which was noticed in one or two 
cases. Plot number one had a slope of from three to five per¬ 
cent. However, it is evident that other factors such as a deep 
and stony condition of the A horizon enter in. 

The sandy condition of plots 11 and 12 of plantation number 
two is undoubtedly the cause of poor growth in these areas. The 
poorest growth took place on the deeper sand. Locke (19^1) 
found the occurrence of oak on sand in the Upper Mississippi 
Valley region to result in poor growth regardless of the size 
or kind of soil particles or the extent to which soil is drained. 
Plots 11 and 12 are well-drained G-ranville soil occurring mostly 
on a gentle slope. 

The regression equation resulting from this study should 
be found of particular use in evaluating land for growth of 
eastern red cedar that has not been previously used for this 
purpose. For a given age up to 15 years, and observing depth 
of surface soil, it should be possible to estimate the height 
(log Y) that will be attained. 


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SUMMARY 


1. Two young eastern red cedar plantations were used in 
this study and data was taken on 73 plots over a total area of 
12.78 acres. Field measurements, field sampling, laboratory 
tests, and statistical analysis were used to determine the 
effect of the following variabless 

a. Depth of the A horizon 

b. Xmblbitional water value of the B horizon. 

2. Statistical analysis showed depth of the A horizon (x£) 
to be highly significant. Age (x^) proved to be significant 
after eliminating X£. The imbibitional water value, when tested 
with other variables was non-significant. 


[ 20 ] 







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Field and Laboratory Data for Plantation 


23 


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OOOOOOOOOOCMOOOOOOOOOOH 


O- CM o CM aaao aooo-o-cmocmo-o-ocmoo 

AVO CM CM O VO CM CM vO O O- CM VO A A O 00 O-AVCVO O 


AOOOCMOOOOOOOOHOHOOOOOO 


AAAA A AACAA A A A 
HHHHHHHHHHrlHHHHHrlrlHrlHH 


O* A CM A O* O- O 0= O-A 0=> O O A ACM A AO-CM A CM 
O CM A-3" vO -d" A AH CM A AO- AVO O H OnAvO On 


NO O-AA-=t C^AAO-AO-AO-H AO OnOnnO 0-0-CM 
H H H H ( 


CM O O-A A CM CM A A O O- CM CM O- A O-A CM O- O-A CM 
O CO 0-0- AACO O O-ANO O-VO A A O AVO CM vO On CM 


O- A A AON A A A A A A AAH ANO C-AON AO-=3- 


054242424242424242 ©4>42 ©42 O O 42 42 42 42 42 © 


rH H H H H H H 

© © H © © H H H H H H H H H H H H H © © © H 
bDbD© J bObD©®©©®©ffl©©©©©®bDbDbD© 

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dddddddddddddddddddddd 

G5GSC55GlG3a5a3GjG5GjcSG5G5G5Gja5G5CijG3q}aSG} 

dddddddddddddddddddddd 

OOOOOOOOOOOOOOOOOOOOOO 


H CM A^" ANO O-CO OnOHcM A-4" AM) 0-00 OnO H CM 

H H rH H rH 1 —! H H r—i H CM CM CM 























Field and Laboratory Data for Plantation 1 (Continued) 


24 


ft 



o 

OVO CO CA 


00 (A CM 


CA0O H CA On 


NO NANA 


CM-3-CO 


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ca u 

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Field and Laboratory Data for Plantation 1 (Continued) 


25 



X3 of 

B 

n horizon 

a 

P Vt 0 

05 

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o 

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a 

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50 © 

erage Average « 

pth of height 

orizon of trees „„ 

ins.) (ft.) yr 

Y 9 ^ 

> © ,£} 

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h c^noo HNoooNr\r\riNinor\w 


d-CO 00 00 ONOVAIMSCO ON CO Os^t^tCX) 
H CM CM H 


OOODCOvOSN.'J-M-i-^- O-d-v© CACN-MO d-VC H 

oo vp, un cj -3- c^nunu^vovo r\^c^or\r\ 
Hc^rinoooNoo o\N4-noooo 

CM 


'-A1NONO WOONiN^IN'A'AOINO 
-3* CN O ==T CM CA CM CM O’N CM CO VO H O 

OOOHOOOHOHHOHOOOO 


(MCMHCMCMHHCOHHHHpHHHOO 

HHHHHHHHHHHHHHHHH 


d-UNd-CMUNOCMD-UNO UN UNO CM d- d- CM 
incniAH on on d- o-v ca un md o-4- h 

M3MDC r \HvOiN'AOr^O\OND»H Ovd-VNCM 
rH H r-1 


d- O UN O- d- O d- CM d~ O CM CM UN CM O d- CM 
O rH d- d- C- CM 00 d- H d- On CM Ov^fr NO 


UN UN CM VO UNvO^j- d-UNd-UNONd-OQ d—^ ON 


t:< 

0 

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H CM ON-^ UNvO d-00 ON O H CM ON-3- UNVO d- 

vp, va un UN UN UN UN UN 


23.31 










































RLAJS/TA T.70A/ 





S£R/£S 


T.R££ d£/GPTS 


[_H Moyo dan ESl 

[11 i IUTI Granv/Z/e ESl 


r H Mayo dan Sl 
1 = 1 Creed/nore SL 

££$^3 Gran v/ZZe S 


0-0 *>4' 
/b - 4 7fe €>' 

C - 6 +08 ' 

d - 8 x>/o‘ 
<z - /Oto/2' 

f - /2> 


Afa/nbtrS /rc//cate average dep/A 

P/of r?u/77her //? red 


SCALE 

















































































































































Field and Laboratory Data for Plantation 


27 


CM 



g 


u o 

0\U-\U-\\Q CM VNvO NOH'nNNH^^ 

O M 

mc^VAlN-H >ACM U-MN-O-OnCO HOOH 

m -h 


r\ u 

C —CXD CO C'-C'-C'-Qn vt^vq o ^ vq oo vo vo 

X o 

eH 

.d 

a 

■p u o 

G O tM 


© H 

C^vo O^- cm c-o^cun- ov^t CM o 0- 0 ov 

p & U 

-3" ON C- CO-4- CM CM 0-0-VO VO vrvvo H CM CM 

U o o 


© o & 

VO CM H CO 00 VOH4HH4-4-H vn-3- CM 

Pk U 

m 

0 « 

• 

bOd . 

NHO O CM VT\ V \ ON O OCD4- O CO 

cti « © 

CM COOnvO CM VO VCNCO OrICM OCO GNrH 

U & c 


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rlHOHHHOOOOOOOOHrl 

> & ^ 
< 


® 05 


fcD-P CD 

©4-iTiHOOO4-OO0 0NHNcncM 

flj © • 

rH vO-3 - C^-C*- O O- On vO VO vO H On H 

U bD U -P 


© -H -J- 3 *M 

H rH ON C*^ rH C°» C^=00 CO VP\ VP\ C*"N ON ON O C^N 

> © w 

rH iH H «H1 Hi HI rH 

O 

<H G 


© o o^-» 


fc>0 © . 

O H 00 O O CO CM UNCO UNrH^ 1 00 O'NCO Os 

aj & «h © 

O H O- O O CN-CM o-rvco CO 

Sh -P U G 

CNVO CM H O-vO OMNO'AA-CAO CM -;}• CO 

© ft o -H 

> © 

(\) H H N H CM H H CM ON (H iH rH rH 

C'd ^ 

<4 


rH 

rH HI rH 

© © H © H 

©©oh 

©©©© iH fflrlHH 

©<M < H<*-i<H®©©©©®® < i-«©©© 
i—1 rH ?-» r~1 £-r rH i—I 

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HciSedaJc4*Ha^«5a-HHct5a5ciJa5 

o 

> f d r O t O f d > r o > r O r d ?> > i O'd ( d , u 

CO 

GOOOOG©GO©GCOOOO 


ctf >s >s >s 5>» aJ © cti >5 © aj c6 >s>»>s>> 
£-ic(SciSctfctS?-tS-)£-«cd?-t?HS-iCda5ctia5 
c!)S2sSiiotSSoc!!Cl!SSgg 

+3 

o 

H CM 0N-3- VT\\0 0-00 ON O H CM ON^t UNvQ 

1—1 

H iH H rH rH rH H 

PL| 













































. 









LITERATURE CITED 





LITERATURE CITED 


Arend, J. L. and R. F. Collins. 

1948. A site classification for eastern red cedar in the 
Ozarks. Proc. Soil Sci. Soc. Amer. r3: 510-511* 

Coile, T. S. 

1948. Relation of soil characteristics to the site index 
of loblolly and shortleaf pines in the lower piedmont 
region of North Carolina. Duke University, School of 
Forestry Bulletin 13 , pp. 57—73• 

Locke, S. S. 

1941. Soil-site factors in predicting timber yields. 
Proc. Soil Sci. Soc. Amer. 6: 399"402. 

Roberts, E. G-. 

1939» Soil depth and height growth of black locust. 

Jour. Forestry 2Z* 583-584. 


[ 29 ] 















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» 

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• 

, 




» 

» 




4 


• 

1 * « 




% • 



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SEEMAN 

PRINTERS AND BINDERS 

DURHAM, N. C.